Porous nitrogen-doped reduced graphene oxide-supported CuO@Cu

Applied sciences Nanomaterials Sensor

Journal

iScience
ISSN: 2589-0042
Titre abrégé: iScience
Pays: United States
ID NLM: 101724038

Informations de publication

Date de publication:
17 Mar 2023
Historique:
received: 17 01 2023
revised: 30 01 2023
accepted: 03 02 2023
entrez: 7 3 2023
pubmed: 8 3 2023
medline: 8 3 2023
Statut: epublish

Résumé

Constructing high-performance enzyme-free biosensors for detecting glucose is essential to preliminary diabetes diagnosis. Here, copper oxide nanoparticles (CuO@Cu

Identifiants

pubmed: 36879815
doi: 10.1016/j.isci.2023.106155
pii: S2589-0042(23)00232-8
pmc: PMC9984959
doi:

Types de publication

Journal Article

Langues

eng

Pagination

106155

Informations de copyright

© 2023.

Déclaration de conflit d'intérêts

The authors declare no competing interests.

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Auteurs

Qing Wei (Q)

Key Laboratory of Biomass-based Materials for Environment and Energy in Petroleum & Chemical Industries, School of Chemical and Environmental Engineering, Wuhan Institute of Technology, Wuhan 430205, China.

Ling Wu (L)

Hubei Province Key Laboratory of Coal Conversion and New Carbon Materials, School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, China.

Meiwen Zhu (M)

Chongqing Academy of Metrology and Quality Inspection, Chongqing 401123, People's Republic of China.

Zhipeng Wang (Z)

Institute of Advanced Materials, Jiangxi Normal University, 99 Ziyang Avenue, Nanchang 330022, China.

Zheng-Hong Huang (ZH)

Lab of Advanced Materials, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China.

Ming-Xi Wang (MX)

Key Laboratory of Biomass-based Materials for Environment and Energy in Petroleum & Chemical Industries, School of Chemical and Environmental Engineering, Wuhan Institute of Technology, Wuhan 430205, China.

Classifications MeSH